dense_tur_mono
This model is a fine-tuned version of on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 4.3321
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 9561
- training_steps: 95611
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0 | 0 | 10.9743 |
| 5.0114 | 1.0458 | 10000 | 5.0269 |
| 4.1953 | 2.0916 | 20000 | 4.3256 |
| 3.8154 | 3.1374 | 30000 | 4.1178 |
| 3.5378 | 4.1832 | 40000 | 4.0507 |
| 3.3222 | 5.2290 | 50000 | 4.0501 |
| 3.0826 | 6.2749 | 60000 | 4.0983 |
| 2.8718 | 7.3207 | 70000 | 4.1736 |
| 2.6672 | 8.3665 | 80000 | 4.2573 |
| 2.4795 | 9.4123 | 90000 | 4.3268 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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